\Header{semat}{Evaluate Kriging Standard Error of Prediction over a Grid}
\keyword{spatial}{semat}
\begin{Description}\relax
Evaluate Kriging standard error of prediction over a grid.\end{Description}
\begin{Usage}
\begin{verbatim}
semat(obj, xl, xu, yl, yu, n, se)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{obj}] object returned by \code{surf.gls}

\item[\code{xl}] limits of the rectangle for grid

\item[\code{xu}] 
\item[\code{yl}] 
\item[\code{yu}] 
\item[\code{n}] use \code{n}  x  \code{n} grid within the rectangle

\item[\code{se}] standard error at distance zero as a multiple of the supplied
covariance. Otherwise estimated, and it assumed that a correlation
function was supplied.

\end{ldescription}
\end{Arguments}
\begin{Value}
list with components x, y and z suitable for \code{contour} and \code{image}.\end{Value}
\begin{References}\relax
Ripley, B. D. (1981) \emph{Spatial Statistics.} Wiley.

Venables, W. N. and Ripley, B. D. (2002)
\emph{Modern Applied Statistics with S.} Fourth edition.  Springer.\end{References}
\begin{SeeAlso}\relax
\code{\Link{surf.gls}}, \code{\Link{trmat}}, \code{\Link{prmat}}\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(topo, package="MASS")
topo.kr <- surf.gls(2, expcov, topo, d=0.7)
prsurf <- prmat(topo.kr, 0, 6.5, 0, 6.5, 50)
contour(prsurf, levels=seq(700, 925, 25))
sesurf <- semat(topo.kr, 0, 6.5, 0, 6.5, 30)
contour(sesurf, levels=c(22,25))
\end{ExampleCode}
\end{Examples}

